High-throughput technologies produce large-scale omics datasets, and their integration facilitates biomarker discovery and predictive modeling. However, challenges such as data heterogeneity, high dimensionality, and block-wise missing data complicate the analysis. To address these issues, optimization techniques, including regularization and constraint-based approaches, have been already employed for regression and binary classification problems. Building on these methods, we extended this framework to support multi-class classification. Indeed, applied to a multi-class classification task for breast cancer subtypes, our model achieves accuracy between 73% and 81% under various block-wise missing data scenarios. Additionally, we assess its performance on a regression problem using the exposome dataset, integrating a larger number of omics datasets. Across different missing data scenarios, our model demonstrates a strong correlation (75%) between true and predicted responses. Furthermore, we have updated the bwm R package, which previously supported binary and continuous response types, to also include multi-class response types.

The antibody response to SARS-CoV-2 does not follow the immunoglobulin isotype pattern of primary responses, conflicting with the current interpretation of COVID-19. METHODS:Prospective cohort study of 191 SARS-CoV-2 infection cases and 44 controls from the second wave of COVID-19. The study stratified patients by severity and analyzed the trajectories of SARS-CoV-2 antibodies and multiple immune variables. RESULTS:Isotype-specific antibody time course profiles to SARS-CoV-2 revealed a pattern of recall response in 94.2 % of cases. The time course profiles of plasmablasts, B cells, cTfh high-resolution subsets, and cytokines indicated a secondary response. The transcriptomic data showed that this cohort is strictly comparable to contemporary cohorts. CONCLUSIONS:In most cases, the immune response to SARS-CoV-2 is a recall response. This constitutes a favorable scenario for most COVID-19 cases to be subjected to immune imprinting by endemic coronavirus, which, in turn, can influence the immune response to SARS-CoV-2.

Biomarkers associated with dietary fibre intake, as complements to traditional dietary assessment tools, may improve the understanding of its role in human health. Our aim was to discover metabolite biomarkers related to dietary fibre intake and investigate their association with cardiometabolic risk factors. We used data and samples from the Danish Diet Cancer and Health Next Generation (DCH-NG) MAX-study, a one-year observational study with evaluations at baseline, six and 12 months (n = 624, 55% female, mean age: 43 years, 1353 observations). Direct associations between fibre intake and plasma concentrations of 2,6-dihydroxybenzoic acid (2,6-DHBA) and indolepropionic acid were observed at the three time-points. Both metabolites showed an intraclass-correlation coefficient (ICC) > 0.50 and were associated with the self-reported intake of wholegrain cereals, and of fruits and vegetables, respectively. Other metabolites associated with dietary fibre intake were linolenoyl carnitine, 2-aminophenol, 3,4-DHBA, and proline betaine. Based on the metabolites associated with dietary fibre intake we calculated predicted values of fibre intake using a multivariate, machine-learning algorithm. Metabolomics-based predicted fibre, but not self-reported fibre values, showed negative associations with cardiometabolic risk factors (i.e. high sensitivity C-reactive protein, systolic and diastolic blood pressure, all FDR-adjusted p-values <0.05). Furthermore, different correlations with gut microbiota composition were observed. In conclusion, 2,6-DHBA and indolepropionic acid in plasma may better link dietary fibre intake with its metabolic effects than self-reported values. These metabolites may represent a novel class of biomarkers reflecting both dietary exposure and host and/or gut microbiota characteristics providing a read-out that is differentially related to cardiometabolic risk.

Hippocampal neurogenesis (HN) occurs throughout the life course and is important for memory and mood. Declining with age, HN plays a pivotal role in cognitive decline (CD), dementia, and late-life depression, such that altered HN could represent a neurobiological susceptibility to these conditions. Pertinently, dietary patterns (e.g., Mediterranean diet) and/or individual nutrients (e.g., vitamin D, omega 3) can modify HN, but also modify risk for CD, dementia, and depression. Therefore, the interaction between diet/nutrition and HN may alter risk trajectories for these ageing-related brain conditions. Using a subsample (n = 371) of the Three-City cohort-where older adults provided information on diet and blood biobanking at baseline and were assessed for CD, dementia, and depressive symptomatology across 12 years-we tested for interactions between food consumption, nutrient intake, and nutritional biomarker concentrations and neurogenesis-centred susceptibility status (defined by baseline readouts of hippocampal progenitor cell integrity, cell death, and differentiation) on CD, Alzheimer's disease (AD), vascular and other dementias (VoD), and depressive symptomatology, using multivariable-adjusted logistic regression models. Increased plasma lycopene concentrations (OR [95% CI] = 1.07 [1.01, 1.14]), higher red meat (OR [95% CI] = 1.10 [1.03, 1.19]), and lower poultry consumption (OR [95% CI] = 0.93 [0.87, 0.99]) were associated with an increased risk for AD in individuals with a neurogenesis-centred susceptibility. Increased vitamin D consumption (OR [95% CI] = 1.05 [1.01, 1.11]) and plasma gamma-tocopherol concentrations (OR [95% CI] = 1.08 [1.01, 1.18]) were associated with increased risk for VoD and depressive symptomatology, respectively, but only in susceptible individuals. This research highlights an important role for diet/nutrition in modifying dementia and depression risk in individuals with a neurogenesis-centred susceptibility.

Stress exposure during the sensitive period of early development has been shown to program the brain and increases the risk to develop cognitive deficits later in life. We have shown earlier that early-life stress (ES) leads to cognitive decline at an adult age, associated with changes in adult hippocampal neurogenesis and neuroinflammation. In particular, ES has been shown to affect neurogenesis rate and the survival of newborn cells later in life as well as microglia, modulating their response to immune or metabolic challenges later in life. Both of these processes possibly contribute to the ES-induced cognitive deficits.Emerging evidence by us and others indicates that early nutritional interventions can protect against these ES-induced effects through nutritional programming. Based on human metabolomics studies, we identified various coffee-related metabolites to be part of a protective molecular signature against cognitive decline in humans. Caffeic and chlorogenic acids are coffee-polyphenols and have been described to have potent anti-oxidant and anti-inflammatory actions. Therefore, we here aimed to test whether supplementing caffeic and chlorogenic acids to the early diet could also protect against ES-induced cognitive deficits.We induced ES via the limited nesting and bedding paradigm in mice from postnatal(P) day 2-9. On P2, mice received a diet to which 0.02% chlorogenic acid (5-O-caffeoylquinic acid) + 0.02% caffeic acid (3’,4’-dihydroxycinnamic acid) were added, or a control diet up until P42. At 4 months of age, all mice were subjected to a behavioral test battery and their brains were stained for markers for microglia and neurogenesis. We found that coffee polyphenols supplemented early in life protected against ES-induced cognitive deficits, potentially this is mediated by the survival of neurons or microglia, but possibly other mechanisms not studied here are mediating the effects. This study provides additional support for the potential of early nutritional interventions and highlights polyphenols as nutrients that can protect against cognitive decline, in particular for vulnerable populations exposed to ES.

Biomedical data are generated and collected from various sources, including medical imaging, laboratory tests and genome sequencing. Sharing these data for research can help address unmet health needs, contribute to scientific breakthroughs, accelerate the development of more effective treatments and inform public health policy. Due to the potential sensitivity of such data, however, privacy concerns have led to policies that restrict data sharing. In addition, sharing sensitive data requires a secure and robust infrastructure with appropriate storage solutions. Here, we examine and compare the centralized and federated data sharing models through the prism of five large-scale and real-world use cases of strategic significance within the European data sharing landscape: the French Health Data Hub, the BBMRI-ERIC Colorectal Cancer Cohort, the federated European Genome-phenome Archive, the Observational Medical Outcomes Partnership/OHDSI network and the EBRAINS Medical Informatics Platform. Our analysis indicates that centralized models facilitate data linkage, harmonization and interoperability, while federated models facilitate scaling up and legal compliance, as the data typically reside on the data generator's premises, allowing for better control of how data are shared. This comparative study thus offers guidance on the selection of the most appropriate sharing strategy for sensitive datasets and provides key insights for informed decision-making in data sharing efforts.

One possible determinant of COVID-19 severity is immune imprinting (IP) by Common Cold Coronavirus (CCCV). As IP occurs only in recall immune responses, we investigated the immune response to SARS-CoV-2 in a cohort of unvaccinated individual to determine whether their immune response aligned with the primary or recall immune response patterns. Analysis of the Ig isotype response trajectories to the Mpro, NP, and S structural proteins and the S RBD in this group of 191 patients and 44 controls revealed a pattern of recall response in 94.2 % of cases. The levels of antibodies correlated positively with the severity of the condition rather than a milder course. High-resolution flow cytometry of fresh PBMNCs showed trajectories of plasmablasts, B cell subsets, and cTfh, suggesting a recall response. The transcriptomic profile demonstrated that this group was directly comparable to other contemporary cohorts. Overall, these findings support the idea that the response to SARS-CoV-2 is, in most cases, a recall response, likely due to B and T memory cells to CCCV, and therefore susceptible to immune imprinting and antibody-dependent enhancement. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by Instituto de Salud Carlos III, Madrid, Spain, grants COV20/00416, Cov20/00654, and COV20/00388 to RP-B, AT-S, and JB-M respectively, and co-financed by the European Regional Development Fund (ERDF). D.A-S is the recipient of a doctoral fellowship from the Vall Hebron Research Institute, Barcelona, Spain (up to 2022 and a postdoctoral fellowship Sara Borrell, CD23/00114 (from 2024). A.S-M was supported by a postdoctoral grant, Juan Rodes (JR18/00022), from Instituto de Salud Carlos III through the Ministry of Economy and Competitiveness, Spain. A.S.P was financially supported by the Spanish Ministerio de Ciencia e Innovacion, grant PID2019-104830RB-I00, and by the Departament Economia i Coneixement de la Generalitat de Catalunya, grant 2017SGR622 (GRBIO). Bioinformatics analysis has been conducted in the Statistics and Bioinformatics Unit (UEB) at Vall Hebron Research Institute (VHIR). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The institutional ethics board approved this project of the three institutions (HUVH: Protocol number PR(AG)242/2020, HUGTP, and HUB. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Anthocyanins (ACNs) are (poly)phenols associated with reduced cardiometabolic risk. Associations between dietary intake, microbial metabolism, and cardiometabolic health benefits of ACNs have not been fully characterized. Our aims were to study the association between ACN intake, considering its dietary sources, and plasma metabolites, and to relate them with cardiometabolic risk factors in an observational study. A total of 1351 samples from 624 participants (55% female, mean age: 45 ± 12 years old) enrolled in the DCH-NG MAX study were studied using a targeted metabolomic analysis. Twenty-four-hour dietary recalls were used to collect dietary data at baseline, six, and twelve months. ACN content of foods was calculated using Phenol Explorer and foods were categorized into food groups. The median intake of total ACNs was 1.6mg/day. Using mixed graphical models, ACNs from different foods showed specific associations with plasma metabolome biomarkers. Combining these results with censored regression analysis, metabolites associated with ACNs intake were: salsolinol sulfate, 4-methylcatechol sulfate, linoleoyl carnitine, 3,4-dihydroxyphenylacetic acid, and one valerolactone. Salsolinol sulfate and 4-methylcatechol sulfate, both related to the intake of ACNs mainly from berries, were inversely associated with visceral adipose tissue. In conclusion, plasma metabolome biomarkers of dietary ACNs depended on the dietary source and some of them, such as salsolinol sulfate and 4-methylcatechol sulfate may link berry intake with cardiometabolic health benefits.

Supplementary Figures 1-8, Supplementary Tables 1-4. Supplementary Figures 1-8: S1: Cell growth as a function of the mutational status of the most frequently mutated genes in colorectal tumors; S2: Independent validation of mRNA expression levels; S3: Correlation between PPOX or GAPDH expression and rates of proliferation in primary tumors; S4: Correlation between drug sensitivity and proliferation rates of colon cancer cells; S5: Effects of acifluorfen and Na iodoacetate on the clonogenic potential of colon cancer cells and induction of apoptosis; S6: Effects of acifluorfen or Na iodoacetate treatment on the cell cycle of colon cancer cells; S7: Effects of PPOX and GAPDH inhibition on the growth of colon cancer cells; S8: Effects of GAPDH and PPOX inhibition on tumor growth using a xenograft model; Supplementary Tables 1-4: S1: Cell lines used in this study; S2: 1593 probes (1,290 unique DAVID IDs) with expression levels significantly correlated with the doubling time of a panel of 31 colorectal cancer cell lines; S3: Functional group enrichment analysis using Gene Ontology categories. Only significantly enriched categories are shown (Benjamini-Hochberg-corrected p<0.05); S4: Associations between PPOX or GAPDH levels and clinicopathological features of a cohort of 433 colorectal tumors from the TCGA.

BACKGROUND:Data for Spain from the Rome Foundation Global Epidemiology Study on the disorders of gut-brain interaction (DGBI) were used to assess the national and regional prevalence of all 22 DGBI, the percentage of respondents meeting diagnostic criteria for at least one DGBI, and the impact on burden of disease in our country. METHODS:Data were collected through an anonymous, nationwide, and secure Internet survey with multiple built-in quality-assurance techniques that included the Rome IV diagnostic questionnaire and an in-depth supplemental questionnaire. KEY RESULTS:The survey was completed by 2072 adult Spanish participants (50.2% female) with a mean age of 45.67 ± 15.44 years with a good representative national distribution. 43.6% (41.5%-45.8%) met diagnostic criteria for at least one DGBI, with 8.2% for any esophageal disorder, 12.1% for any gastroduodenal disorder, 30.1% for any bowel disorder, and 11.5% for any anorectal disorder. Functional constipation was the most prevalent DGBI in Spain (12.8%). We found that proctalgia fugax (9.3%), unspecified bowel disorders (10.8%), and functional dysphagia (5.6%) showed unexplained high rates in our country. DGBI rates were higher for women. Having any DGBI was negatively associated with psychosocial variables (including quality of life, somatization, and concern about digestive problems), and associated with increased healthcare utilization. CONCLUSIONS & INFERENCES:We provide the first comprehensive data on the prevalence and burden of all DGBI in Spain using the Rome IV criteria. The enormous burden of DGBI in Spain highlights the need for specialized training and future research.

Introduction:During the development of Autoimmune Diabetes (AD) an autoimmune attack against the Peripheral Nervous System occurs. To gain insight into this topic, analyses of Dorsal Root Ganglia (DRG) from Non-Obese Diabetic (NOD) mice were carried out.Methods:Histopathological analysis by electron and optical microscopy in DRG samples, and mRNA expression analyzes by the microarray technique in DRG and blood leukocyte samples from NOD and C57BL/6 mice were performed.Results:The results showed the formation of cytoplasmic vacuoles in DRG cells early in life that could be related to a neurodegenerative process. In view of these results, mRNA expression analyses were conducted to determine the cause and/or the molecules involved in this suspected disorder. The results showed that DRG cells from NOD mice have alterations in the transcription of a wide range of genes, which explain the previously observed alterations. In addition, differences in the transcription genes in white blood cells were also detected.Discussion:Taken together, these results indicate that functional defects are not only seen in beta cells but also in DRG in NOD mice. These results also indicate that these defects are not a consequence of the autoimmune process that takes place in NOD mice and suggest that they may be involved as triggers for its development.

Description Statistical tests for label-free LC-MS/MS data by spectral counts, to discover differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package.The three models admit blocking factors to control for nuissance vari-ables.To assure a good level of reproducibility a post-test filter is avail-able, where we may set the minimum effect size considered biologicaly relevant, and the minimum expression of the most abundant condition. Statistical tests for label-free LC-MS/MS data by spectral counts, to discover differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package. The three models admit blocking factors to control for nuissance variables. To assure a good level of reproducibility a post-test filter is available, where we may set the minimum effect size considered biologicaly relevant, and the minimum expression of the most abundant condition.

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences.

BACKGROUND AND OBJECTIVES:To identify biomarkers associated with treatment response in patients with multiple sclerosis (MS) treated with the oral therapies teriflunomide, dimethyl fumarate (DMF), and fingolimod.METHODS:Serum levels of IL-6, IL-17, TNF-α, granulocyte-macrophage colony-stimulating factor, IL-10, interferon-gamma (IFN-γ) IL-1β, and chemokine ligand 13 (CXCL13) were measured at baseline and 12 months with single molecule array (Simoa) assays in a cohort of patients with MS treated with teriflunomide (N = 19), DMF (N = 22), and fingolimod (N = 25) and classified into "no evidence of disease activity" (NEDA) and EDA patients after 1 year of treatment.RESULTS:Serum CXCL13 and TNF-α levels were significantly decreased after treatment with teriflunomide in NEDA compared with EDA patients after 1 year of treatment (p = 0.008 for both cytokines). These findings were validated in an independent cohort of patients with MS treated with teriflunomide (N = 36) and serum CXCL13, and TNF-α levels were again significantly reduced in NEDA patients (p < 0.0001 for CXCL13 and p = 0.003 for TNF-α). CXCL13, but not TNF-α, showed good performance to classify NEDA and EDA patients according to a cut-off value of 9.64 pg/mL based on the change in CXCL13 levels between baseline and 12 months, with a sensitivity of 75% and specificity of 82% in the original cohort, and sensitivity of 65.4% and specificity of 60% in the validation cohort.DISCUSSION:Altogether, these results point to CXCL13 as a treatment response biomarker to teriflunomide in relapsing-remitting patients with MS, and the change in CXCL13 levels during the first year of treatment can be used in clinical practice to identify optimal responders to teriflunomide.

The aim of this study was to assess the effects of a mixture of four dietary fibers on obese rats. Four groups of male Wistar rats were fed with either standard chow (STD) or cafeteria diet (CAF) and were orally supplemented with either fibre mixture (2 g kg−1 of body weight) (STD+F or CAF+F groups) or vehicle (STD+VH or CAF+VH groups). We studied a wide number of biometric, biochemical, transcriptomic, metagenomic and metabolomic variables and applied an integrative multivariate approach based on multiple factor analysis and Pearson's correlation analysis. A significant reduction in body weight, adiposity, HbA1c and HDL-cholesterol serum levels, and colon MPO activity was observed, whereas cecal weight and small intestine length:weight ratio were significantly increased in F-treated groups compared to control animals. CAF+F rats displayed a significant enhancement in energy expenditure, fat oxidation and fresh stool weight, and a significant reduction in adiponectin and LPS serum levels, compared to control group. Animals in STD+F group showed reduced serum LDL-cholesterol levels and a significant reduction in total cholesterol levels in the liver compared to STF+VH group. The intervention effect was reflected at the metabolomic (i.e., production of short-chain fatty acids, phenolic acids, and amino acids), metagenomic (i.e., modulation of Ruminococcus and Lactobacillus genus) and transcriptomic (i.e., expression of tight junctions and proteolysis) levels. Altogether, our integrative multi-omics approach highlights the potential of supplementation with a mixture of fibers to ameliorate the impairments triggered by obesity in terms of adiposity, metabolic profile, and intestinal health.

Scope: Evidence on the Mediterranean diet (MD) and age-related cognitive decline (CD) is still inconclusive partly due to self-reported dietary assessment. The aim of the current study is to develop an MD- metabolomic score (MDMS) and investigate its association with CD in community-dwelling older adults.Methods and results: This study includes participants from the Three-City Study from the Bordeaux (n = 418) and Dijon (n = 422) cohorts who are free of dementia at baseline. Repeated measures of cognition over 12 years are collected. An MDMS is designed based on serum biomarkers related to MD key food groups and using a targeted metabolomics platform. Associations with CD are investigated through conditional logistic regression (matched on age, sex, and education level) in both sample sets. The MDMS is found to be inversely associated with CD (odds ratio [OR] [95% confidence interval (CI)] = 0.90 [0.80-1.00]; p = 0.048) in the Bordeaux (discovery) cohort. Results are comparable in the Dijon (validation) cohort, with a trend toward significance (OR [95% CI] = 0.91 [0.83-1.01]; p = 0.084).Conclusions: A greater adherence to the MD, here assessed by a serum MDMS, is associated with lower odds of CD in older adults.

Background and aims: Plant-based dietary patterns have been associated with improved health outcomes. This study aims to describe the metabolomic fingerprints of plant-based diet indices (PDI) and examine their association with metabolic syndrome (MetS) and its components in a Danish population.Methods: The MAX study comprised 676 participants (55% women, aged 18-67 y) from Copenhagen. Socio-demographic and dietary data were collected using questionnaires and three 24-h dietary recalls over one year (at baseline, and at 6 and 12 months). Mean dietary intakes were computed, as well as overall PDI, healthful (hPDI) and unhealthful (uPDI) scores, according to food groups for each plant-based index. Clinical variables were also collected at the same time points in a health examination that included complete blood tests. MetS was defined according to the International Diabetes Federation criteria. Plasma metabolites were measured using a targeted metabolomics approach. Metabolites associated with PDI were selected using random forest models and their relationships with PDIs and MetS were analyzed using generalized linear mixed models.Results: The mean prevalence of MetS was 10.8%. High, compared to low, hPDI and uPDI scores were associated with a lower and higher odd of MetS, respectively [odds ratio (95%CI); hPDI: 0.56 (0.43-0.74); uPDI: 1.61 (1.26-2.05)]. Out of 411 quantified plasma metabolites, machine-learning metabolomics fingerprinting revealed 13 metabolites, including food and food-related microbial metabolites, like hypaphorine, indolepropionic acid and lignan-derived enterolactones. These metabolites were associated with all PDIs and were inversely correlated with MetS components (p < 0.05). Furthermore, they had an explainable contribution of 12% and 14% for the association between hPDI or uPDI, respectively, and MetS only among participants with overweight/obesity.Conclusions: Metabolites associated with PDIs were inversely associated with MetS and its components, and may partially explain the effects of plant-based diets on cardiometabolic risk factors.

IntroductionLittle is known about the molecular profiling associated with the effect of cladribine in patients with multiple sclerosis (MS). Here, we aimed first to characterize the transcriptomic and proteomic profiles induced by cladribine in blood cells, and second to identify potential treatment response biomarkers to cladribine in patients with MS. MethodsGene, protein and microRNA (miRNA) expression profiles were determined by microarrays (genes, miRNAs) and mass spectrometry (proteins) in peripheral blood mononuclear cells (PBMCs) from MS patients after in vitro treatment with cladribine in its active and inactive forms. Two bioinformatics approaches to integrate the three obtained datasets were applied: (i) a multiomics discriminant analysis (DIABLO - Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies); and (ii) a multi-stage integration of features selected in differential expression analysis on each dataset and then merged. Selected molecules from the in vitro study were quantified by qPCR ex vivo in PBMCs from MS patients receiving cladribine. ResultsPBMCs treated in vitro with cladribine were characterized by a major downregulation of gene, protein, and miRNA expression compared with the untreated cells. An intermediate pattern between the cladribine-treated and untreated conditions was observed in PBMCs treated with cladribine in its inactive form. The differential expression analysis of each dataset led to the identification of four genes and their encoded proteins, and twenty-two miRNAs regulating their expression, that were associated with cladribine treatment. Two of these genes (PPIF and NHLRC2), and three miRNAs (miR-21-5p, miR-30b-5p, and miR-30e-5p) were validated ex vivo in MS patients treated with cladribine. DiscussionBy using a combination of omics data and bioinformatics approaches we were able to identify a multiomics molecular profile induced by cladribine in vitro in PBMCs. We also identified a number of biomarkers that were validated ex vivo in PBMCs from patients with MS treated with cladribine that have the potential to become treatment response biomarkers to this drug.